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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

2018 Renewable Energy Grid Integration Data Book

The 2018 Renewable Energy Grid Integration Data Book identifies the status, key trends, challenges, and solutions of renewable energy grid integration in a highly visual format. It provides an overview of selected key grid integration metrics that represent complex interactions among generation characteristics, market rules, and environmental and safety factors, which may vary by geography, season, and time of day; and the data book presents metrics that either indicate how much variable renewable energy (VRE) is currently being integrated onto the grid or measure factors that may increase or decrease the challenges associated with integrating VRE generation onto the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Multi-omic data integration enables discovery of hidden biological regularities

Rapid growth in size and complexity of biological data sets has led to the ‘Big Data to Knowledge’ challenge. We develop advanced data integration methods for multi-level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome-scale models, based on genomic and bibliomic data, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can be formally represented in a computable format allowing for coherent interpretation and prediction of fitness and selection that underlies cellular physiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Bioinformatics Resource Manager: A systems biology web tool for microRNA and omics data integration

Background: The Bioinformatics Resource Manager (BRM) is a web-based tool developed to facilitate identifier conversion and data integration for Homo sapiens (human), Mus musculus (mouse), Rattus norvegicus (rat), Danio rerio (zebrafish), and Macaca mulatta (macaque), as well as perform orthologous conversions among the supported species. In addition to providing a robust means of identifier conversion, BRM also incorporates a suite of miRNA-target databases upon which to query target genes or to perform reverse target lookups using gene identifiers. Results: BRM has the capability to perform cross-species identifier lookups across common identifier types, directly integrate datasets across platform or species by performing identifier retrievals in the background, and retrieve miRNA targets from multiple databases simultaneously and integrate the resulting gene targets with experimental mRNA data. Here we use workflows provided in BRM to integrate RNAseq data across species to identify common biomarkers of exposure after treatment of human lung cells and zebrafish to benzo[a]pyrene (BAP). We further use the miRNA Target workflow to experimentally determine the role of miRNAs as regulators of BAP toxicity and identify the predicted functional consequences of miRNA-target regulation in our system. The output from BRM can easily and directly be uploaded to freely available visualization tools for further analysis. From these examples, we were able to identify an important role for several miRNAs as potential regulators of BAP toxicity in human lung cells associated with cell migration, cell communication, cell junction assembly and regulation of cell death. Conclusions: Overall, BRM provides bioinformatics tools to assist biologists having minimal programming skills with analysis and integration of high-content omics’ data from various transcriptomic and proteomic platforms. BRM workflows were developed in Java and other open-source technologies and are served publicly using Apache Tomcat at https://cbb.pnnl.gov/brm/.

bioinformatics, MicroRNA, systems biology, Genomic↗
DOE OSTI2020

Data Integration Aggregated Model For Nuclear Deployment

The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often needed and is performed manually and on an as-needed basis. The integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data model contains objects that make up a given domain along with their attributes and relationships and could be used as a standard for exchange between applications for simple integration and data aggregation. After a survey of existing models, it was determined that a new model was required to meet the scope of this problem. DIAMOND has been developed in the form of an ontology to meet these needs. An ontology is simply a data model that also acts as a taxonomy for the domain, organizing the objects in a hierarchy with the most general objects at the top.

Browning, JerenM↗
DOE OSTI2020

Detection and Diagnosis of Data Integrity Attacks in Solar Farms Based on Multilayer Long Short-Term Memory Network

Photovoltaic (PV) systems are becoming more vulnerable to cyber threats. In response to this emerging concern, developing cyber-secure power electronics converters has received increased attention from the IEEE Power Electronics Society that recently launched a cyber-physical-security initiative. Here this letter proposes a deep sequence learning based diagnosis solution for data integrity attacks on PV systems in smart grids, including dc–dc and dc–ac converters. The multilayer long short-term memory networks are used to leverage time-series electric waveform data from current and voltage sensors in PV systems. The proposed method has been evaluated in a PV smart grid benchmark model with extensive quantitative analysis. As a comparison, we have evaluated classic data-driven methods, including K-nearest neighbor, decision tree, support vector machine, artificial neural network, and convolutional neural network. Comparison results verify performances of the proposed method for detection and diagnosis of various data integrity attacks on PV systems.

42 ENGINEERING↗
DOE OSTI2020

Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel

Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Differential and Integral Data Evaluation for Titanium: An Application to Criticality Safety

The intent of this work is to highlight the role of differential and integral data evaluation to address issues in connection with criticality safety applications. Demonstration is made by using, as an example, differential data measurements and evaluation, and the benchmark integral experiments for titanium. Energy differential data are measured analyzed and evaluated to produce nuclear data libraries for criticality safety applications. Alternatively, integral experiments are performed at critical facilities, small experimental reactors, and play an important part in the validation of the differential nuclear data. The demonstration provided here for titanium gives its importance to criticality safety. Titanium is an effective neutron absorber that serves as baseline material for chemical separation in high-activity waste solutions in US. Titanium has not been considered for use in nuclear applications such as reactor design and analysis. Rather, it appears as a structural material that may be present in fuel cycle facilities or canisters for transport and disposition of nuclear waste. Criticality safety evaluations of systems in which titanium is present require an understanding of the nuclear data and its uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Impact Analysis of Data Integrity Attacks on FACTS-based Wide-Area Voltage Control System

Energy management system (EMS) consists of several wide-area control applications that serve as a backbone for security, stability, and reliability of the power system. Wide-area voltage control system (WAVCS), one of the critical wide-area applications, operates in coordination with local Flexible AC Transmission System (FACTS) devices to provide voltage security and optimal management of active and reactive power resources. Since the WAVCS relies on wide-area communication and data sharing devices, possible cybersecurity vulnerabilities have to be addressed to ensure the closed-loop operation of WAVCS. In this paper, we present a methodology for performing an impact analysis of cyber-attacks in WAVCS cybersecurity. In particular, different types of data integrity attacks, such as malicious tripping, fault replay, and signal altering attacks, are considered, and detailed impact analysis is conducted in a testbed environment using the Kundur's four machine two-area system. For performing an impact analysis, the transient voltage stability of the sensitive bus voltage is studied, followed by the quantitative assessment and severity ranking using the voltage profile index. Our experimental evaluation reveals that the data integrity attacks on control signals exhibit a higher attack severity than on the measurement signals. Further, the severity of these attacks varies with nature (static or dynamic), location, and types of attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Using integrated data analysis to extend measurement capability (invited)

The analysis approach called integrated data analysis (IDA) provides a means to exploit all information present in multiple streams of raw data to produce the best inference of a plasma parameter. This contrasts with the typical approach in which information (data) from a single diagnostic is used to measure a given parameter, e.g., visible bremsstrahlung → Z eff . Data from a given diagnostic usually contain information on many parameters. For example, a Thomson scattering diagnostic is sensitive to bremsstrahlung and line emission in addition to electron temperature. This background light is typically subtracted off and discarded but could be used to improve knowledge of Z eff . IDA encourages explicit awareness of such information and provides the quantitative framework to exploit it. This gives IDA the ability to increase spatial and temporal resolution, increase precision and accuracy of inferences, and measure plasma parameters that are difficult or impossible to measure using single diagnostic techniques. One example is the measurement of Z eff on Madison symmetric torus using IDA since no single diagnostic can provide a robust measurement. Thus, as we enter the burning plasma era, application of IDA will be critical to the measurement of certain parameters, as diagnostic access in the harsh fusion environment will be extremely limited.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND): Preliminary Model and Ontology

The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often performed manually and on an as-needed basis to achieve a targeted cost saving. A holistic approach to the integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data warehouse results in direct and indirect cost saving because it automates the manual search for data, enables sharing and comparison of data from various tools of a single or multiple plants, enable digital transformation of data, increase frequencies of needed data that are sparse in nature (such as failures signatures), reduces the need for training on various tools for plant staff, enables a holistic staff perception of plant activities, reveals cost-saving opportunities, and improves the visual perception of all parts a plant necessary for operations and maintenance. One of the main challenges to deploy a data warehouse is associated with the integration of data sources into a consistent data model using a standard ontology that is developed by and for the nuclear power industry. This model is non-existent and is a necessity to enable the nuclear data warehouse role. A data model contains objects that make up a given domain along with their attributes and relationships. It provides domain standardization and maintainability, setting forth the objects, attributes, and relationships within that domain and acting as the guide by which the various applications within that domain will structure their data and interchange. An ontology is defined as “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them”. Ontologies consist of a taxonomy or directed rooted tree. A survey of the models and ontologies available to support a data integration aggregated model and ontology for nuclear deployment (DIAMOND) was performed and different standards that address specific aspects of the needed model and ontology were leveraged and integrated in this effort. In specific, the Basic Formal Ontology (BFO) and Lifecycle Modeling Language (LML) were leveraged for the base ontology. The ISO 4224 and 15926 were leveraged in the development of the overlapping nuclear and fossil data aspects. The electric power research institute (EPRI) power distribution common information model (CIM) was also reviewed and the experience gained was leveraged in the power generation scope of DIAMOND. The initial aim targeted by this effort was to develop the ontology definitions and model structure. This report documents the resulting model and ontology to develop DIAMOND. The report describes the various elements of the model development based on a growing tree development approach, i.e. DIAMOND’s tree structure is established with the core data aspects and is populated with a preliminary level of details. Fifteen sources of data in a nuclear power plant were considered and incorporated into DIAMOND at this stage of development, representing the majority of operations data sources in nuclear power plants. Additional data sources, scope, and a higher level of fidelity will be incorporated into DIAMOND next in collaboration with the nuclear industry and relevant stakeholders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Blockchain Based Remote Data Integrity Checking Tool v1.0

Computer System Security: The software is used to perform remote data integrity checking without relying on a single third party. In order to remove the trusted third party our tool uses distributed ledger (Blockchain) technology. The ledger is used to store evidences (in the form of hash values). These values are used as an input in the integrity checking process.

Wonjiga, Amir↗
DOE OSTI2019

Bayesian Monte-Carlo Evaluation Framework of Differential and Integral Data [Slides]

This presentation discusses the Bayesian Monte Carlo evaluation framework of differential and integral data, specifically in relation to two methods that are based on Bayes theorem, which assumes that all PDFs are normal (Gaussian) and that they use a linear approximation for IBEs. The presentation states that basic components of the MC evaluation framework include the computation of random MC ensemble from ENDF File 32, the simulation of IBEs and R-matrix cross section compared to experimental data, and the computation of weighted averages. It also states that the application to U-233 indicates deviation from the conventional linear approximation. In conclusion, evaluation framework will require MCMC method e.g., Metropolis-Hastings (M.-H.).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Low Yield Nuclear Monitoring Physics Experiment 1 – Integrated Data Acquisition System Design and Initial Observations

The report documents the design of the Integrated Data AcQuisition (IDAQ) system and observations recorded during the first in a series of underground chemical explosions conducted on the Nevada National Security Site (NNSS) in southern Nevada. Experiments are funded as part of Low Yield Nuclear Monitoring (LYNM) research and development within the United States National Nuclear Security Administration NA-22 nuclear non-proliferation program. The series is part of the broader Physical Experiment 1 (PE1) being conducted in and around the P-tunnel facility on the NNSS. Each explosive experiment utilizes several tons of comp-B to generate signals recorded by a broad suite of instrumentation. The IDAQ serves as the backbone for all subsurface instrumentation providing precise time synchronization, remote control, data exfiltration and backup, along with recording several sensing modalities throughout the underground complex that includes ground motion, environmental conditions, and electromagnetic signals.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗